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Approximation of dynamic system vector field using neural networks in approximate aircraft attainability domain construction problem
Engineering Education # 08, August 2011
DOI: 10.7463/0811.0204143
Dynamic system attainability domain approximate construction problem based on “multi-finish” and model differential equation system vector field approximation methods combination is discussed. The main point of the first method is multiple model differential equation system integration with different controls values. The idea of the second method is preliminary approximation  of model differential equation system’s right side. The purpose of this article is to find out the efficiency of neural network approximation. The research is carried out for 7th order differential equation system, which describes aircraft center-of-mass motion. Three-layer feed-forward neural network and similar cascaded neural network are analyzed.
Dynamic system attainability domain boundaries construction via composition of multiple integration and vector field approximation approaches
Engineering Education # 05, May 2011
DOI: 10.7463/0511.0185335
Dynamic system attainability domain approximate construction problem is considered. We studyefficiency of using composition of multiple integration approach and vector field approximation of model differential equations system for solution of this problem. We present description of specified methods and their tests on application of approximate construction of attainability domain of aircraft, described by model. For given research we reach a conclusion about usability condition of approach composition involved.
 
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